TY  - JOUR
AB  - Purpose The purpose of this paper is to develop some picture uncertain linguistic aggregation operators based on Bonferroni mean operators, which is combined with multiple attribute decision-making (MADM) and has applied the proposed MADM model for selecting the service outsourcing provider of communications industry under picture uncertain linguistic environment.Design/methodology/approach The service outsourcing provider selection problem of communications industry can be regarded as a typical MADM problem, in which the decision information should be aggregated. In this paper, the authors investigate the MADM problems with picture uncertain linguistic information based on traditional Bonferroni mean operator.Findings The results show that the proposed model can solve the MADM problems within the context of picture uncertain linguistic information, in which the attributes are existing interaction phenomenon. Some picture uncertain aggregation operators based on Bonferroni mean have been developed. A case study of service outsourcing provider selection problem of communications industry is provided to illustrate the effectiveness and feasibility of the proposed methods. The results show that the proposed methods are useful to aggregate the picture uncertain linguistic decision information in which the attributes are not independent so as to select the most suitable supplier.Research limitations/implications The proposed methods can solve the picture uncertain linguistic MADM problem, in which the interactions exist among the attributes. Therefore, it can be used to solve service outsourcing provider selection problems and other similar management decision problems.Practical implications This paper develops some picture uncertain aggregation operators based on Bonferroni mean and further presents two methods based on the proposed operators for solving MADM problems. It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.Social implications It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.Originality/value The paper investigates the MADM problems with picture uncertain linguistic information based on traditional Bonferroni mean operator and develops the picture uncertain linguistic Bonferroni mean operator and picture uncertain linguistic geometric Bonferroni mean operator, picture uncertain linguistic weighted Bonferroni mean operator and picture uncertain linguistic weighted geometric Bonferroni mean operator for aggregating the picture uncertain linguistic information, respectively. Finally, a numerical example concerning the service outsourcing provider selection problem of communications industry is provided to illustrate the effectiveness and feasibility of the proposed methods.
VL  - 46
IS  - 10
SN  - 0368-492X
DO  - 10.1108/K-01-2017-0025
UR  - https://doi.org/10.1108/K-01-2017-0025
AU  - Wei Guiwu
PY  - 2017
Y1  - 2017/01/01
TI  - Picture uncertain linguistic Bonferroni mean operators and their application to multiple attribute decision making
T2  - Kybernetes
PB  - Emerald Publishing Limited
SP  - 1777
EP  - 1800
Y2  - 2024/09/23
ER  -